A mathematical model is presented relating the presence of NO 2 in the oxidant stream to the fuel cell performance loss. Both contamination and recovery processes are considered. The model is validated using cell voltage/current density distribution and cell voltage change as a function of NO 2 concentration transient data. The model is used to discuss NO 2 threshold concentrations and contaminant screening. General and NO 2 specific gaps in contaminant characterization methodology are also highlighted.

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Administration of a high reloading dose of atorvastatin within 24 hours before PCI could significantly reduce the frequency of periprocedural MI. CLINICAL TRIAL REGISTRATION CODE: IRCT201205209768N1.

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This paper proposes a novel passivity cascade technique (PCT)-based control for nonlinear inverted pendulum systems. Its main objective is to stabilize the pendulum’s upward states despite uncertainties and exogenous disturbances. The proposed framework combines the estimation properties of radial basis function neural networks (RBFNs) with the passivity attributes of the cascade control framework. The unknown terms of the nonlinear system are estimated using an RBFN approximator. The performance of the closed-loop system is further enhanced by using the integral of angular position as a virtual state variable. The lumped uncertainties (NN—Neural Network approximation, external disturbances and parametric uncertainty) are compensated for by adding a robustifying adaptive rule-based signal to the PCT-based control. The boundedness of the states is confirmed using the passivity theorem. The performance of the proposed approach was assessed using a nonlinear inverted pendulum system under both nominal and disturbed conditions.

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